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I am Shreyash Wetal, an Artificial Intelligence Engineer and Researcher specializing in Machine Learning, Deep Learning, Computer Vision, and Large Language Models. I design, train, optimize, and deploy scalable AI systems that improve accuracy, reduce latency, and boost production performance across healthcare, surveillance, and enterprise automation. I have hands-on experience with Retrieval-Augmented Generation, transformer fine-tuning, semantic segmentation, MLOps, ETL pipelines, and cloud deployment on GCP. I am passionate about building production-ready architectures and solving real-world problems with data-driven, memory-efficient AI solutions.…I am Shreyash Wetal, an Artificial Intelligence Engineer and Researcher specializing in Machine Learning, Deep Learning, Computer Vision, and Large Language Models. I design, train, optimize, and deploy scalable AI systems that improve accuracy, reduce latency, and boost production performance across healthcare, surveillance, and enterprise automation. I have hands-on experience with Retrieval-Augmented Generation, transformer fine-tuning, semantic segmentation, MLOps, ETL pipelines, and cloud deployment on GCP. I am passionate about building production-ready architectures and solving real-world problems with data-driven, memory-efficient AI solutions.

Shreyash Wetal

AI Engineer, Data Scientist, AI Developer, +2

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I am Shreyash Wetal, an Artificial Intelligence Engineer and Researcher specializing in Machine Learning, Deep Learning, Computer Vision, and Large Language Models. I design, train, optimize, and deploy scalable AI systems that improve accuracy, reduce latency, and boost production performance across healthcare, surveillance, and enterprise automation. I have hands-on experience with Retrieval-Augmented Generation, transformer fine-tuning, semantic segmentation, MLOps, ETL pipelines, and cloud deployment on GCP. I am passionate about building production-ready architectures and solving real-world problems with data-driven, memory-efficient AI solutions.…I am Shreyash Wetal, an Artificial Intelligence Engineer and Researcher specializing in Machine Learning, Deep Learning, Computer Vision, and Large Language Models. I design, train, optimize, and deploy scalable AI systems that improve accuracy, reduce latency, and boost production performance across healthcare, surveillance, and enterprise automation. I have hands-on experience with Retrieval-Augmented Generation, transformer fine-tuning, semantic segmentation, MLOps, ETL pipelines, and cloud deployment on GCP. I am passionate about building production-ready architectures and solving real-world problems with data-driven, memory-efficient AI solutions.

Available to hire

I am Shreyash Wetal, an Artificial Intelligence Engineer and Researcher specializing in Machine Learning, Deep Learning, Computer Vision, and Large Language Models. I design, train, optimize, and deploy scalable AI systems that improve accuracy, reduce latency, and boost production performance across healthcare, surveillance, and enterprise automation.

I have hands-on experience with Retrieval-Augmented Generation, transformer fine-tuning, semantic segmentation, MLOps, ETL pipelines, and cloud deployment on GCP. I am passionate about building production-ready architectures and solving real-world problems with data-driven, memory-efficient AI solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Research Student (Artificial Intelligence) at University of Sydney

March 1, 2025 - Present

Designed and trained deep CNN architectures for medical image semantic segmentation, improving Dice score by 12%. Implemented preprocessing, augmentation, and cross-validation pipelines increasing model generalization across datasets. Performed hyperparameter tuning using grid and Bayesian optimization, reducing validation loss by 18%. Benchmarked U-Net and DeepLabV3+ architectures, optimizing inference efficiency and robustness. Automated evaluation workflows using IoU, F1-score, precision-recall, and ROC metrics for reproducible experimentation.

Artificial Intelligence Engineer (Team Lead) at The Modern Group

June 1, 2025 - December 31, 2025

Architected and deployed LLM-based systems using RAG pipelines and vector retrieval, focusing on long-term contextual information retrieval and memory-efficient conversational AI systems, improving retrieval accuracy by 30%. Designed prompt engineering and LLM decision pipelines for context-aware reasoning and data-driven decision support systems, increasing contextual relevance by 25%. Built scalable real-time inference APIs integrated with Firebase and GCP, reducing deployment cycle time by 40%. Designed ETL pipelines and dimensional data models supporting analytics for 100K+ records. Reduced inference latency and cloud costs by 20% through model optimization and batching strategies. Led AI lifecycle management including experimentation, CI/CD integration, deployment, and monitoring.

Associate Prompt Engineer at NVIDIA

October 1, 2024 - December 31, 2024

Engineered enterprise-grade prompt frameworks improving LLM response precision by 22%. Conducted structured A/B testing across multiple transformer architectures to enhance output consistency. Applied reinforcement learning feedback strategies to improve generation reliability. Developed automated prompt evaluation pipelines to standardize NLP benchmarking.